Peder Engelstad

About Me

I am a Research Associate in the Vogeler Lab and a PhD student in the Graduate Degree Program in Ecology at Colorado State University in Fort Collins, CO. I am also the primary developer on the Invasive Species Habitat Tool (INHABIT), a web-based decision support tool hosted by the USGS.

My current research focus on species distribution modeling through the development of novel model assessment and extrapolation approaches, with a focus on terrestrial invasive plants species. Through these approaches I hope to improve our understanding the spatial processes underlying plant invasions and expand the utility of models for invasive species management.

 

Education

PhD Ecology Colorado State University 2026 (Anticipated)
MS Watershed Science Colorado State University 2018
BA Anthropology University of Wisconsin-Madison 2006

 

Publications


Peer-Reviewed Journal Articles
  1. Evans, A.E., Jarnevich, C.S., Beaury, E.M., Engelstad, P.S., Teich, N.B., LaRoe, J.M., & Bradley, B.A. (2023). Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance habitats. Diversity and Distributions, ddi.13787. https://doi.org/10.1111/ddi.13787

  2. Burner, R.C., Daniel, W.M., Engelstad, P.S., Churchill, C.J., & Erickson, R.A. (2023). BioLake: A First Assessment of Lake Temperature-Derived Bioclimatic Predictors for Aquatic Invasive Species. Ecosphere 14(7): e4616. https://doi.org/10.1002/ecs2.4616

  3. Beaury, E.M., Jarnevich, C.S., Pearse, I., Evans, A.E., Teich, N., Engelstad, P., LaRoe, J., & Bradley, B.A. (2023). Modeling habitat suitability across different levels of invasive plant abundance. Biological Invasions 1-13. https://doi.org/10.1007/s10530-023-03118-z

  4. Jarnevich, C., Engelstad, P., LaRoe, J., Hays, B., Hogan, T., Jirak, J., Pearse, I., Prevéy, J., Sieracki, J., Simpson, A., Wenick, J., Young, N., & Sofaer, H. R. (2023). Invaders at the doorstep: Using species distribution modeling to enhance invasive plant watch lists. Ecological Informatics, 101997. https://doi.org/10.1016/j.ecoinf.2023.101997

  5. Engelstad P., Jarnevich C.S., Hogan T., Sofaer H.R., Pearse I.S., et al. (2022). INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States. PLOS ONE 17(2): e0263056. https://doi.org/10.1371/journal.pone.0263056

  6. Erickson, R.A., Engelstad, P.S., Jarnevich, C.S., Sofaer, H.R., & Daniel, W.M. (2022). Climate matching with the climatchR R package. Environmental Modelling & Software, 10551 https://doi.org/10.1016/j.envsoft.2022.105510

  7. Jarnevich, C.S., Sofaer H.R., Engelstad P., & Belamaric, P. (2022). Regional models do not outperform continental models for invasive species. Neobiota. https://doi.org/10.3897/neobiota.77.86364

  8. Jarnevich, C.S., Sofaer, H.R., & Engelstad, P. (2021). Modelling presence versus abundance for invasive species risk assessment. Diversity and Distributions, 27(12), 2454-2464. https://doi.org/10.1111/ddi.13414

  9. Young, N.E., Jarnevich, C.S., Sofaer, H.R., Pearse, I., Sullivan, J., Engelstad, P., & Stohlgren, T.J. (2020). A modeling workflow that balances automation and human intervention to inform invasive plant management decisions at multiple spatial scales. PLOS ONE, 15(3), e0229253. https://doi.org/10.1371/journal.pone.0229253

  10. Engelstad, P.S., Falkowski, M.J., D’Amato, A.W., Slesak, R.A., Palik, B.J., Domke, G.M. & Russell, M.B. (2019). Mapping black ash dominated stands using geospatial and forest inventory data in northern Minnesota, USA. Canadian Journal of Forest Research, 48(8), 892-902. https://doi.org/10.1139/cjfr-2018-0481

  11. Engelstad, P.S., Falkowski, M., Wolter, P., Poznanovic, A., & Johnson, P. (2019). Estimating canopy fuel attributes from low-density LiDAR. Fire, 2(3), 38. https://doi.org/10.3390/fire2030038

  12. Woodward, B., Engelstad, P., Vorster, A., Beddow, C., Krail, S., Vashisht, A., & Evangelista, P. (2017). Forest harvest dataset for northern Colorado Rocky Mountains (1984–2015) generated from a Landsat time series and existing forest harvest records. Data in brief, 15, 724-727. https://doi.org/10.1016/j.dib.2017.10.030



Book Chapters

  1. Engelstad, P., Carver, D., & Young, N. E. (2024). Creating Presence and Absence Points. In J. A. Cardille, M. A. Crowley, D. Saah, & N. E. Clinton (Eds.), Cloud-Based Remote Sensing with Google Earth Engine (pp. 1133–1155). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_52

  2. Engelstad, P., Carver, D., & Young, N. E. (2024). Working with GPS and Weather Data. In J. A. Cardille, M. A. Crowley, D. Saah, & N. E. Clinton (Eds.), Cloud-Based Remote Sensing with Google Earth Engine (pp. 1121–1131). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_51



Software & Datasets

  1. Engelstad P., Jarnevich, C., Sofaer, H., Daniel, W., Peterman, L., Erickson, R.A. (2023). climatchR: An implementation of CLIMATCH in R. v2.0. U.S. Geological Survey software release. Reston, VA. https://doi.org/10.5066/P9ILPPTC

  2. Jarnevich, C.S., LaRoe, J., Engelstad, P., Hays, B., Henderson, G., Williams, D., Shadwell, K., Pearse, I.S., Prevey, J.S., & Sofaer, H.R. (2023). INHABIT species potential distribution across the contiguous United States (ver. 3.0, February 2023): U.S. Geological Survey data release. https://doi.org/10.5066/P9V54H5K

  3. Evans, A., Beaury, E.M., Engelstad, P.S., Teich, N.B., & Bradley, B.A. (2022). Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance ranges. Data and Datasets. 157. https://doi.org/10.7275/f172-4c95


Peder Engelstad

About Me

I am a Research Associate in the Vogeler Lab and a PhD student in the Graduate Degree Program in Ecology at Colorado State University in Fort Collins, CO. I am also the primary developer on the Invasive Species Habitat Tool (INHABIT), a web-based decision support tool hosted by the USGS.

My current research focus on species distribution modeling through the development of novel model assessment and extrapolation approaches, with a focus on terrestrial invasive plants species. Through these approaches I hope to improve our understanding the spatial processes underlying plant invasions and expand the utility of models for invasive species management.

 

Education

PhD Ecology Colorado State University 2026 (Anticipated)
MS Watershed Science Colorado State University 2018
BA Anthropology University of Wisconsin-Madison 2006

 

Publications


Peer-Reviewed Journal Articles
  1. Evans, A.E., Jarnevich, C.S., Beaury, E.M., Engelstad, P.S., Teich, N.B., LaRoe, J.M., & Bradley, B.A. (2023). Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance habitats. Diversity and Distributions, ddi.13787. https://doi.org/10.1111/ddi.13787

  2. Burner, R.C., Daniel, W.M., Engelstad, P.S., Churchill, C.J., & Erickson, R.A. (2023). BioLake: A First Assessment of Lake Temperature-Derived Bioclimatic Predictors for Aquatic Invasive Species. Ecosphere 14(7): e4616. https://doi.org/10.1002/ecs2.4616

  3. Beaury, E.M., Jarnevich, C.S., Pearse, I., Evans, A.E., Teich, N., Engelstad, P., LaRoe, J., & Bradley, B.A. (2023). Modeling habitat suitability across different levels of invasive plant abundance. Biological Invasions 1-13. https://doi.org/10.1007/s10530-023-03118-z

  4. Jarnevich, C., Engelstad, P., LaRoe, J., Hays, B., Hogan, T., Jirak, J., Pearse, I., Prevéy, J., Sieracki, J., Simpson, A., Wenick, J., Young, N., & Sofaer, H. R. (2023). Invaders at the doorstep: Using species distribution modeling to enhance invasive plant watch lists. Ecological Informatics, 101997. https://doi.org/10.1016/j.ecoinf.2023.101997

  5. Engelstad P., Jarnevich C.S., Hogan T., Sofaer H.R., Pearse I.S., et al. (2022). INHABIT: A web-based decision support tool for invasive plant species habitat visualization and assessment across the contiguous United States. PLOS ONE 17(2): e0263056. https://doi.org/10.1371/journal.pone.0263056

  6. Erickson, R.A., Engelstad, P.S., Jarnevich, C.S., Sofaer, H.R., & Daniel, W.M. (2022). Climate matching with the climatchR R package. Environmental Modelling & Software, 10551 https://doi.org/10.1016/j.envsoft.2022.105510

  7. Jarnevich, C.S., Sofaer H.R., Engelstad P., & Belamaric, P. (2022). Regional models do not outperform continental models for invasive species. Neobiota. https://doi.org/10.3897/neobiota.77.86364

  8. Jarnevich, C.S., Sofaer, H.R., & Engelstad, P. (2021). Modelling presence versus abundance for invasive species risk assessment. Diversity and Distributions, 27(12), 2454-2464. https://doi.org/10.1111/ddi.13414

  9. Young, N.E., Jarnevich, C.S., Sofaer, H.R., Pearse, I., Sullivan, J., Engelstad, P., & Stohlgren, T.J. (2020). A modeling workflow that balances automation and human intervention to inform invasive plant management decisions at multiple spatial scales. PLOS ONE, 15(3), e0229253. https://doi.org/10.1371/journal.pone.0229253

  10. Engelstad, P.S., Falkowski, M.J., D’Amato, A.W., Slesak, R.A., Palik, B.J., Domke, G.M. & Russell, M.B. (2019). Mapping black ash dominated stands using geospatial and forest inventory data in northern Minnesota, USA. Canadian Journal of Forest Research, 48(8), 892-902. https://doi.org/10.1139/cjfr-2018-0481

  11. Engelstad, P.S., Falkowski, M., Wolter, P., Poznanovic, A., & Johnson, P. (2019). Estimating canopy fuel attributes from low-density LiDAR. Fire, 2(3), 38. https://doi.org/10.3390/fire2030038

  12. Woodward, B., Engelstad, P., Vorster, A., Beddow, C., Krail, S., Vashisht, A., & Evangelista, P. (2017). Forest harvest dataset for northern Colorado Rocky Mountains (1984–2015) generated from a Landsat time series and existing forest harvest records. Data in brief, 15, 724-727. https://doi.org/10.1016/j.dib.2017.10.030



Book Chapters

  1. Engelstad, P., Carver, D., & Young, N. E. (2024). Creating Presence and Absence Points. In J. A. Cardille, M. A. Crowley, D. Saah, & N. E. Clinton (Eds.), Cloud-Based Remote Sensing with Google Earth Engine (pp. 1133–1155). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_52

  2. Engelstad, P., Carver, D., & Young, N. E. (2024). Working with GPS and Weather Data. In J. A. Cardille, M. A. Crowley, D. Saah, & N. E. Clinton (Eds.), Cloud-Based Remote Sensing with Google Earth Engine (pp. 1121–1131). Springer International Publishing. https://doi.org/10.1007/978-3-031-26588-4_51



Software & Datasets

  1. Engelstad P., Jarnevich, C., Sofaer, H., Daniel, W., Peterman, L., Erickson, R.A. (2023). climatchR: An implementation of CLIMATCH in R. v2.0. U.S. Geological Survey software release. Reston, VA. https://doi.org/10.5066/P9ILPPTC

  2. Jarnevich, C.S., LaRoe, J., Engelstad, P., Hays, B., Henderson, G., Williams, D., Shadwell, K., Pearse, I.S., Prevey, J.S., & Sofaer, H.R. (2023). INHABIT species potential distribution across the contiguous United States (ver. 3.0, February 2023): U.S. Geological Survey data release. https://doi.org/10.5066/P9V54H5K

  3. Evans, A., Beaury, E.M., Engelstad, P.S., Teich, N.B., & Bradley, B.A. (2022). Shifting hotspots: Climate change projected to drive contractions and expansions of invasive plant abundance ranges. Data and Datasets. 157. https://doi.org/10.7275/f172-4c95